1 Answers
Three basic KF generalizations for nonlinear systems:
- Extended Kalman filter (EKF): Analytic linearization of model at each point in time: problematic, but still popular.
- Sigma-point (Unscented) Kalman filter (SPKF/UKF): Statistical/empirical linearization of the model at each point in time: can be much better than EKF at the same computational complexity.
- Particle filters: Most precise, but often thousands of times more computations required than either EKF/SPKF.